mindspore.ops.poisson

mindspore.ops.poisson(shape, mean, seed=None)[source]

Generates random numbers according to the Poisson random number distribution.

\[\text{P}(i|μ) = \frac{\exp(-μ)μ^{i}}{i!}\]
Parameters

  • shape (tuple) – The shape of random tensor to be generated. The format is \((N,*)\) where \(*\) means, any number of additional dimensions.

  • mean (Tensor) – The mean μ distribution parameter. It should be greater than 0 with float32 data type.

  • seed (int) – Seed is used as entropy source for the random number engines to generate pseudo-random numbers and must be non-negative. Default: None, which will be treated as 0.

Returns

Tensor. The shape should be equal to the broadcasted shape between the input “shape” and shapes of mean. The dtype is float32.

Raises

  • TypeError – If shape is not a tuple.

  • TypeError – If mean is not a Tensor whose dtype is not float32.

  • TypeError – If seed is not an int.

Supported Platforms:

Ascend

Examples

>>> # case 1: It can be broadcast.
>>> shape = (4, 1)
>>> mean = Tensor(np.array([5.0, 10.0]), mindspore.float32)
>>> output = ops.poisson(shape, mean, seed=5)
>>> result = output.shape
>>> print(result)
(4, 2)
>>> # case 2: It can not be broadcast. It is recommended to use the same shape.
>>> shape = (2, 2)
>>> mean = Tensor(np.array([[5.0, 10.0], [5.0, 1.0]]), mindspore.float32)
>>> output = ops.poisson(shape, mean, seed=5)
>>> result = output.shape
>>> print(result)
(2, 2)